Abstract Ride-sourcing services are getting more popular each year, and their markets are growing. Much has been speculated, but not much has been tested regarding the impacts of ride-sourcing services on the transportation system. In this study, we examine the relationship between ride-sourcing services and vehicle ownership of households, by using the most up-to-date (2017) national household travel survey data. To better capture the effect of ride-sourcing services on vehicle ownership, we controlled for the effect of socioeconomic characteristics of households and built environment variables, i.e., density, diversity, design, and distance to transit. Two approaches were used to model vehicle ownership: a probabilistic or inferential model (i.e., multilevel Poisson), and a machine learning method (i.e., random forest). This is the first study to utilize such advanced methods to model vehicle ownership and capture non-linear relationships, using the largest sample of household travel records ever assembled for such a study. The results suggest that there is a negative correlation between using ride-sourcing services and vehicle ownership. Vehicle ownership is also negatively associated with the number of years Uber, as the biggest ride-sourcing service, has operated in a county. The relative contributions of ride-sourcing variables, however, are very limited compared to other variables controlled in this study which makes intuitive sense. For urban planning and design practices, this study suggests that the probability of car shedding will increase if the usage of ride-sourcing services becomes a habit, these services become more available, and built environments become more dense, connected, and transit-served.

中文翻译：

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使用推理和机器学习方法探索打车服务与车辆所有权之间的关系

摘要 拼车服务每年都越来越受欢迎，其市场也在不断增长。关于拼车服务对交通系统的影响，已经有很多猜测，但没有得到太多测试。在本研究中，我们通过使用最新（2017 年）全国家庭旅行调查数据，研究了拼车服务与家庭车辆拥有量之间的关系。为了更好地捕捉拼车服务对车辆拥有量的影响，我们控制了家庭社会经济特征和建筑环境变量的影响，即密度、多样性、设计和交通距离。使用两种方法对车辆所有权进行建模：概率或推理模型（即多级泊松）和机器学习方法（即随机森林）。这是第一项利用此类先进方法对车辆所有权进行建模并捕捉非线性关系的研究，使用有史以来为此类研究收集的最大家庭旅行记录样本。结果表明，使用拼车服务与车辆拥有量之间存在负相关。车辆拥有量也与优步作为最大的打车服务公司在一个县运营的年数呈负相关。然而，与本研究中控制的其他变量相比，乘车服务变量的相对贡献非常有限，这具有直观意义。对于城市规划和设计实践，这项研究表明，如果使用拼车服务成为一种习惯，这些服务变得更加可用，那么汽车脱落的可能性就会增加，